發(fā)布時間：2020-12-20 08:18

　　棉花是重要經(jīng)濟作物,在許多國家的國民經(jīng)濟中發(fā)揮著重要作用。棉纖維是紡織業(yè)主要材料來源,也是決定棉花經(jīng)濟價值的重要部分。全球人口基數(shù)的增大和人們生活水平的提高對纖維產(chǎn)量和品質(zhì)提出了更高的要求。因此選育出高產(chǎn)、優(yōu)質(zhì)的棉花新品種成為棉花育種學(xué)家當(dāng)前至關(guān)重要的任務(wù)。但棉花的纖維品質(zhì)是受多個等位基因控制的復(fù)雜數(shù)量性狀,極易受環(huán)境影響,并且纖維品質(zhì)與產(chǎn)量之間存在一定的負(fù)相關(guān)關(guān)系。因此,利用傳統(tǒng)的育種方法培育高產(chǎn)優(yōu)質(zhì)棉花進展緩慢。隨著生物學(xué)技術(shù)的進步,分子標(biāo)記輔助選擇育種被逐漸應(yīng)用于棉花的育種研究,這為改良棉花的纖維品質(zhì)和產(chǎn)量提供了新的解決方案。遺傳圖譜構(gòu)建和QTL有利等位基因鑒定是分子標(biāo)記輔助選擇育種的兩個主要組成部分。隨著生物學(xué)技術(shù)和測序技術(shù)的進步,用于構(gòu)建遺傳圖譜的分子標(biāo)記逐漸從傳統(tǒng)的分子標(biāo)記（如SSR標(biāo)記）向SNP標(biāo)記和In Del標(biāo)記轉(zhuǎn)變。以SNP標(biāo)記構(gòu)建的遺傳圖譜,普遍具有高密度的特征,能夠有效應(yīng)用于分子標(biāo)記輔助選擇育種。而以簡化基因組測序技術(shù)（SLAF-seq）獲取SNP標(biāo)記是目前應(yīng)用最廣泛的方法�；谝粡埜呙芏冗z傳連鎖圖譜,在多環(huán)境和多世代下鑒定棉花的纖維相關(guān)QTL,能夠為棉花的纖維... 

【文章來源】：西南大學(xué)重慶市 211工程院校 教育部直屬院校

【文章頁數(shù)】：75 頁

【學(xué)位級別】：博士

【文章目錄】：
摘要
Abstract
Chapter 1 Introduction
    1.1 Classification and diversity of cotton
        1.1.1 Classification of cotton
        1.1.2 Genetic diversity of cotton
    1.2 Structure and formation of cotton fiber
        1.2.1 Chemical composition of cotton fiber
        1.2.2 Physical characterization of cotton fiber
        1.2.3 Measurements of cotton fiber
        1.2.4 Maturity of cotton fiber
    1.3 Genetic factors controlling fiber traits
    1.4 Importance of molecular markers
        1.4.1 Advantages of molecular markers
        1.4.2 PCR based markers properties
    1.5 Genotyping
        1.5.1 Genotyping through traditional markers
        1.5.2 Genotyping through SLAF-seq
    1.6 Research development of MAS in cotton
Character 2 Materials and Methods
    2.1 Plant materials and construction of the RIL population
    2.2 Total DNA extraction
        2.2.1 Procedures of DNA extraction
    2.3 SSR markers genotyping
        2.3.1 Source of SSR markers
        2.3.2 Amplification system of SSR primers
        2.3.3 Polyacrylamide gel electrophoresis
    2.4 SLAF-SNP creation,and sequencing
    2.5 Genetic map construction
    2.6 Phenotype analysis
    2.7 QTL analysis
    2.8 QTL by environment interaction（QEI）analysis
    2.9 Technical route
Chapter 3 Results
    3.1 Phenotypic data analysis
    3.2 Obtation of SNP and SSR markers
    3.3 High-density genetic map construction
    3.4 Physical length of the genetic map
    3.5 QTL identification for fiber related traits
        3.5.1 QTLs for lint percentage
        3.5.2 QTLs for fiber length
        3.5.3 QTLs for fiber strength
        3.5.4 QTLs for fiber micronaire
        3.5.5 QTLs for fiber uniformity
        3.5.6 QTLs for fiber elongation
    3.6 QTL clusters
    3.7.QTL by environment interaction analysis
Character 4 Discussion
    4.1 Selection of molecular markers
    4.2 QTL identification
    4.3 The direction of favorable QTL alleles
Character 5 Conclusion
    5.1 Construction of the high-density genetic map
    5.2 Identification of QTLs for fiber related traits
    5.3 Identification of QTL clusters
Reference
Acknowledgement


【參考文獻】：
期刊論文
[1]QTL IciMapping:Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations[J]. Lei Meng,Huihui Li,Luyan Zhang,Jiankang Wang.  The Crop Journal. 2015(03)
[2]陸地棉衣分及相關(guān)性狀的遺傳和QTL分子標(biāo)記[J]. 張培通,朱協(xié)飛,郭旺珍,張?zhí)煺?  江蘇農(nóng)業(yè)學(xué)報. 2005(04)



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